KYC's getting harder, but it's necessary to avoid an onboarding crisis

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In a previous column for PaymentsSource, I explained why too many banks are doing the bare minimum to stop money laundering. As a result, financial institutions face hefty operational costs, while also being unable to capture the necessary customer data to identify, rank-order and manage risk efficiently or effectively.

Last year, the U.S. Financial Crimes Enforcement Network strengthened Customer Due Diligence (CDD) mandates, requiring financial institutions to dip deeper into their customer data to risk-rank them. These activities are tedious, time consuming and often redundant, creating long onboarding times and less-than-stellar customer experiences.

Banks can benefit from following the three steps below to successfully build and implement an end-to-end onboarding and KYC solution. These best practices will ensure consistency across the enterprise.
Ensure data quality. The quality of data has a large impact on the success of KYC processes, so make the necessary adjustments, such as completing risk profiles. This will allow your team to define a new target operating model and new business processes.

Automate the populating and risk-ranking of customer information. Using Robotic Process Automation, bots can extract the required client/entity information from multiple data sources, populate the necessary fields for Ultimate Beneficial Ownership development and fill in customer information in seconds—rather than days—to perform the required CDD and Enhanced Due Diligence tasks.

Leverage advanced analytics and artificial intelligence. This will allow banks to identify and address patterns that create false positives and an enormous backlog of alerts, which have a negative impact on customer satisfaction. AI also allows for a much wider variety of data and use models to adjust more quickly to patterns of “good,” which will reduce false positives without reducing sensitivity to true issues.

A flexible, secure, and enterprise-scale KYC solution will enable a quick onboarding process and also support an automated risk assessment, due diligence and remediation of an existing customer back-book.

Recently, a European bank faced similar issues with siloed onboarding and KYC processes controlled by each line of business, which caused inconsistencies across customer segments and products. The leadership team invested in an anti-money laundering transformation to help automate the approach, which remediates the backlog of existing customers and complies with the new directive’s requirements, while also ensuring the appropriate levels of discovery and risk assessment at the outset of every new and existing customer relationship.

As a result of solving the regulatory compliance deficiencies, the aforementioned European bank experienced a 40% reduction in onboarding costs, 30% improvement in relationship managers’ bandwidth, and greater than 90% STP rates for onboarding.

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